File size: 6,827 Bytes
630930b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 |
import os
import pandas as pd
import urllib3
import json
from bs4 import BeautifulSoup
import numpy as np
from concurrent.futures import ThreadPoolExecutor
from concurrent.futures import Future
from traitlets import List
from reddit.reddit_info import subreddit_name_l, subreddit_sort_l, subreddit_t_l
import itertools
import random
from pathlib import Path
from tqdm import tqdm
from datetime import datetime, timezone
from typing import Any, Optional
from requests.utils import requote_uri
from random_word import RandomWords
from wonderwords import RandomSentence
class RedditProcessor:
def get_subreddit_url(self, subreddit, sort_by:str = "hot", sort_time:str="all", limit:int=100, query:Optional[str]=None):
if not query:
return f'https://www.reddit.com/r/{subreddit}/{sort_by}/.json?raw_json=1&t={sort_time}&limit={limit}'
else:
return f'https://www.reddit.com/r/{subreddit}/search/.json?raw_json=1&q={query}&limit={100}'
def fetch_subreddit_image_entries(self, subreddit_url: str, pool_manager):
result = [ ]
try:
response = pool_manager.request('GET', subreddit_url)
#print(response.data)
subreddit_data = json.loads(response.data)
if not "data" in subreddit_data: return []
if not "children" in subreddit_data["data"]: return []
for content in subreddit_data['data']['children']:
try:
if content['data'].get('post_hint', 'none') == 'image' and 'preview' in content['data']:
created_utc = datetime.fromtimestamp(content['data']["created_utc"], timezone.utc)
#print(created_utc)
source_d = content['data']['preview']['images'][0]['source']
image_url, width, height = source_d['url'], source_d["width"], source_d["height"]
image_title = content['data']['title']
image_id = content['data']['id']
data_url = content['data']['url']
subreddit = content['data']['subreddit']
if content['data']['is_video'] : continue
result.append({
"image_url" : image_url,
"title" : image_title,
"image_id" : image_id,
"url" : data_url,
"subreddit" : subreddit,
"width" : width,
"height" : height,
"created_utc" : created_utc,
})
except Exception as e:
pass
return result
except Exception as e:
#print(e)
return []
def fetch_multiple_subreddit_image_entries(self, subreddit_urls: str, thread_pool_size: int=5, urllib_pool_size:int=5):
pool_manager = urllib3.PoolManager(maxsize=urllib_pool_size)
thread_pool = ThreadPoolExecutor(thread_pool_size)
res_futs = [ ]
for subreddit_url in subreddit_urls:
res_futs.append(thread_pool.submit(self.fetch_subreddit_image_entries, subreddit_url, pool_manager))
res :[List[Future]] = []
for r in res_futs:
res.extend(r.result())
return list({x["image_id"] : x for x in res}.values())
def get_random_subreddit_urls(self, num_urls:int = 20):
subr_l = list(itertools.product(subreddit_name_l, subreddit_sort_l, subreddit_t_l))
return [self.get_subreddit_url(*xs, 100) for xs in random.sample(subr_l, k=num_urls)]
def get_random_subreddit_query_urls(self, num_urls:int = 20, query_type: str = "chronology"):
'''
query_type:
chronology
random_word
random_phrase
'''
timeline = random.choices(["days", "months", "years"], k = num_urls)
timevalue = random.choices(range(1, 12), k = num_urls)
subr = random.sample(subreddit_name_l, k = num_urls)
if query_type == "chronology":
return [self.get_subreddit_url(subreddit=sr, query=f"{tv} {tl} ago") for (sr, tl, tv) in list(itertools.product(subr, timeline, timevalue))]
elif query_type == "random_word":
r = RandomWords()
return [self.get_subreddit_url(subreddit=sr, query=f"{r.get_random_word()}") for sr in subr]
elif query_type == "random_phrase":
s = RandomSentence()
return [self.get_subreddit_url(subreddit=sr, query=f"{s.sentence()}") for sr in subr]
else:
return [ ]
def __call__(self, reddit_out_file: os.PathLike) -> Any:
dfname = reddit_out_file
otime = 0
tarr = []
karr = []
total_updates = 0
with tqdm(total=10000) as pbar:
for _ in range(10000):
if random.random() > 0.6:
res = self.fetch_multiple_subreddit_image_entries(self.get_random_subreddit_urls(num_urls=100))
else:
res = self.fetch_multiple_subreddit_image_entries(
self.get_random_subreddit_query_urls(num_urls=5, query_type="random_phrase"))
num_fetched = len(res)
if res:
if not Path(dfname).exists():
pd.DataFrame(res).to_csv(dfname, index=False)
karr.append(len(res))
else:
df = pd.read_csv(dfname)
keys = set(df["image_id"])
cres = [x for x in res if not (x["image_id"] in keys)]
if cres:
ndf = pd.DataFrame(cres)
ndf.to_csv(dfname, mode="a", header=None, index=False)
karr.append(len(cres))
else:
karr.append(0)
ntime = pbar.format_dict['elapsed']
N = len(pd.read_csv(dfname))
tarr.append(ntime-otime)
otime = ntime
tarr = tarr[-25:]
karr = karr[-25:]
rate = sum(karr)/sum(tarr)
pbar.update(1)
total_updates = total_updates + karr[-1]
pbar.set_description_str(f"count:{N}, fetch rate:{rate:.3f}, last_update:{karr[-1]}, total_updates:{total_updates}") |